Perceptions and attitudes of medical oncologists regarding fertility preservation and pregnancy in high‐risk cancer patients: A survey among Canadian medical oncologists
Bibliographic record
Abstract
PURPOSE: Infertility is a critical late toxicity that impacts adolescent and young adult (AYA, ages 15-39 years) cancer survivors. International oncology societies recommend discussing fertility preservation (FP) for all AYA patients, regardless of stage or prognosis. We aim to understand Canadian medical oncologists' perceptions, attitudes, and knowledge toward FP and pregnancy in patients with cancer, including advanced stages and high risk for recurrence. METHODS: An anonymous electronic survey utilizing hypothetical scenarios was sent to medical oncologists in the province of Ontario, Canada. Descriptive statistics were used to summarize all data. Logistic regression models were constructed to identify factors that predicted FP discussions and referrals. RESULTS: The survey was received by 91 medical oncologists, and the response rate was 44%. Fifty-eight percent of respondents offer FP for all patients. Physicians are more likely to refer patients for FP before curative intent therapy than before palliative chemotherapy (95% vs. 39.5%, p < 0.001). Most respondents (86%) are comfortable discussing FP; however, only 31% self-reported feeling up-to-date on knowledge of current FP methods. Female physicians were more likely to report up-to-date knowledge and confidence discussing FP with patients. Forty percent of respondents identified that concerns about the welfare of the resulting offspring should not be a cause for denying patients assistance in reproduction. CONCLUSION: There is a significant difference in physician attitude toward offering FP based on the cancer stage. Increased awareness of standard of care guidelines and resources for difficult situations may improve the frequency of discussions about FP in motivated cancer patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".